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A Bayesian longitudinal model for quantifying students' preferences regarding teaching quality indicators

机译：贝叶斯纵向模型，用于量化关于教学质量指标的学生偏好

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The aim of the paper is to estimate the posterior mean values and analyze the posterior variation in students' prioritization of teaching quality components within a 10-year frame, The results are based on longitudinal data gathered among Greek university students during the period of the national economic crisis in Greece spanned from 2009 to 2018, The analysis consists of fitting a Bayesian hierarchical beta regression model with a Dirichlet prior on the model coefficients that correspond to twenty quality attribute measures. Using this natural way to implement the usual constraints, the model coefficients can be interpreted as weights and thus they measure the relative importance that the students give to the different attributes. By estimating the posterior means and positioning measures of all consecutive sampling instances and summarizing posterior distributions of the differences between consecutive periods in the model weights, the study identifies and evaluates the major changes and patterns in students' perception of academic quality over the ten-year sampling period.
机译：本文的目的是估算后平均值，并分析了学生在10年内教学质量成分的优先级的后续变化，结果基于全国期间希腊大学生聚集的纵向数据希腊的经济危机从2009年到2018年跨越，分析包括将贝叶斯分层Beta回归模型与Dirichlet符合在模型系数上，与二十个质量属性措施相对应。使用这种自然方法来实现通常的约束，模型系数可以被解释为权重，因此它们测量学生给出不同属性的相对重要性。通过估计所有连续采样实例的后部手段和定位措施，并概述模型权重中连续时段之间的差异的后分布，研究确定并评估了学生对十年学术素质的看法的重大变化和模式抽样期。

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